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Study On The Sustained High-level Energy Consumption In China

Posted on:2018-05-17Degree:MasterType:Thesis
Country:ChinaCandidate:Q C WangFull Text:PDF
GTID:2382330518459095Subject:Energy Economics
Abstract/Summary:PDF Full Text Request
The rebound effect of energy consumption in China has been the focus of attention in the theoretical fields and it has not yet to form a unified opinion.Under the new normal,we pay more attention to the quality of economic development,which requires that the energy consumption of the unit economic output should be gradually reduced,and at the same time the energy efficiency is continually improving.According to?China's energy policy 2012?,it has risen to the height of China's national energy policy that to realize the target of energy saving by improving energy efficiency.But can we significantly reduce energy consumption solely by improving energy efficiency?This question was first proposed by the British marginalist economist William Stanley Jevons.He pointed out that more energy demand will derived from technology induced energy efficiency,thus energy consumption will not decline but to rise.Thus the claim was later known as the "Jevons Paradox".It needs further study that whether "Jevons Paradox" is applicable to energy consumption in China.Based on the theory of"Learning by Doing" that was proposed by Arrow,this paper builds an endogenous growth model using nested production function from the perspective of output maximizing.This paper deduces the theoretical estimation model of energy consumption rebound effect under the conditions that labor supply is exogenous but energy efficiency is endogenous.Next this paper prepare to use the time series data of energy consumption,capital,real output and labor in China from 1952 to 2015 to get the value of energy rebound effect for each period in China.The main contributions of this paper are as follows:Firstly,from the perspective of maximizing output,energy efficiency is endogenously determined in the theoretical model which is the based on endogenous growth theory.Secondly,this paper uses time series data of energy consumption,capital investment,labor input and output to measure China's energy rebound at different times and then this paper will judge whether China's energy consumption fall into Jevons Paradox.Thirdly,from the perspective of the rigid demand for economic growth,this paper reveals the further reason that why China's energy consumption sink into Jevons Paradox.Results indicate that the output elasticity of energy and learning effect are the key to influence the direction of energy rebound effect in the short run.In the long run,in addition to the output elasticity of energy and learning effect,even the substitution elasticity between capital and labor,the output elasticity of capital as well as the combined output elasticity of capital and labor are also the factors that influence the magnitude of energy rebound effect.China's data show that,during the period of 1952-2015 the average rebound effect is 131.6%and the highest rebound effect is 216.4%.According to these results,this paper conclude that China's energy consumption gets stuck with Jevons Paradox.Thus it is infeasible to rely solely on improving energy efficiency to reduce energy consumption.In the long run,the average rebound effect of China's energy consumption is 204.7%and the highest is 960.6%during the period of 1952-2015.And there are sometimes a super energy-saving periods or partial energy saving periods.The macroeconomic level of China's energy consumption may be out of Jevons Paradox,and potential of energy saving is huge.In this paper,the empirical results show that China's energy consumption gets stuck with Jevons Paradox.And the further reason is the rigid demand of national economy.In order to get rid of Jevons Paradox,we should seek the optimal equilibrium between technological progress which is measured by energy efficiency and the rate of change in real output.
Keywords/Search Tags:Energy consumption, Jevons Paradox, Nested model, Endogenous growth
PDF Full Text Request
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